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Media Contacts
![An X-ray CT image of a 3D-printed metal turbine blade was reconstructed using ORNL’s neural network and advanced algorithms. Credit: Amir Ziabari/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-01/Manufacturing%20-%20Defect%20detection%202_0.jpg?h=259e5a75&itok=CwpLQv6U)
Algorithms developed at Oak Ridge National Laboratory can greatly enhance X-ray computed tomography images of 3D-printed metal parts, resulting in more accurate, faster scans.
![Distinguished Inventors](/sites/default/files/styles/list_page_thumbnail/public/2020-12/inventors.jpg?h=4631f1c1&itok=xhAGY0kv)
Six scientists at the Department of Energy’s Oak Ridge National Laboratory were named Battelle Distinguished Inventors, in recognition of obtaining 14 or more patents during their careers at the lab.
![Paul Kent, shown above posing with Summit in April 2018, received the 2020 ORNL Director’s Award for Outstanding Individual Accomplishment in Science and Technology. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-11/DA_Kent.jpg?h=48cf6540&itok=Ocw9WcgV)
The annual Director's Awards recognized four individuals and teams including awards for leadership in quantum simulation development and application on high-performance computing platforms, and revolutionary advancements in the area of microbial
![ORNL Sign](/sites/default/files/styles/list_page_thumbnail/public/2020-11/ORNLsign.jpg?h=22d0129c&itok=YoZbTjCS)
Seven ORNL scientists have been named among the 2020 Highly Cited Researchers list, according to Clarivate, a data analytics firm that specializes in scientific and academic research.
![Tony Schmitz, UT/ORNL joint faculty researcher in machine tooling, has been elected to the College of Fellows of the American Society for Precision Engineering. Credit: Carlos Jones, Oak Ridge National Laboratory/U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-10/Engineering_Portrait_ORNL-0224_0.jpg?h=790be497&itok=UczyQkhA)
Tony Schmitz, joint faculty researcher in machining and machine tools at Oak Ridge National Laboratory, and mechanical, aerospace and biomedical engineering professor at the University of Tennessee, Knoxville, has been elected to the College of Fellows of the American Society for Precision Engineering.
![ORNL researchers and energy storage startup Sparkz have developed a cobalt-free cathode material for use in lithium-ion batteries Credit: Ilias Belharouak/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-10/cobalt-sparkz_0.jpg?h=cd715a88&itok=vTU2FKUY)
Four research teams from the Department of Energy’s Oak Ridge National Laboratory and their technologies have received 2020 R&D 100 Awards.
![3D printed EMPOWER wall drawing](/sites/default/files/styles/list_page_thumbnail/public/2020-08/EMP_WALL11.jpg?h=1d9512c1&itok=3Q-UnrTY)
Oak Ridge National Laboratory researchers used additive manufacturing to build a first-of-its kind smart wall called EMPOWER.
![Hector J. Santos-Villalobos, left, and Oscar A. Martinez](/sites/default/files/styles/list_page_thumbnail/public/2020-08/henaac20.jpg?h=158d9140&itok=-NxooIrE)
Two staff members at the Department of Energy’s Oak Ridge National Laboratory have received prestigious HENAAC and Luminary Awards from Great Minds in STEM, a nonprofit organization that focuses on promoting STEM careers in underserved
![SPRUCE experiment](/sites/default/files/styles/list_page_thumbnail/public/2020-08/SPRUCE_0.png?h=9afda364&itok=zCibJUsI)
Oak Ridge National Laboratory scientists evaluating northern peatland responses to environmental change recorded extraordinary fine-root growth with increasing temperatures, indicating that this previously hidden belowground mechanism may play an important role in how carbon-rich peatlands respond to warming.
![Map with focus on sub-saharan Africa](/sites/default/files/styles/list_page_thumbnail/public/2020-07/firms3-Africa-NASA_0.jpg?h=27f1d52b&itok=G8uUS5cH)
Researchers at Oak Ridge National Laboratory developed a method that uses machine learning to predict seasonal fire risk in Africa, where half of the world’s wildfire-related carbon emissions originate.